Senior Data Engineer

Role Purpose

The Senior Data Engineer is responsible for helping establish and operate the organization’s data platform, turning business information into reliable, governed, and reusable data. This is a hands-on role for someone who can work independently, make sound technical decisions, and take ownership from requirements through production support. Working closely with the Data Platform and Engineering Lead, the role will build integrations, data models, quality controls, monitoring, and engineering practices that enable reporting, analytics, decision-making, automation, and AI. The role offers the opportunity to solve important data challenges, shape the engineering capability, and build foundations that will grow with the organization. 

• Own the design, development, testing, release, operation, and support of reliable data pipelines and platform components. 

• Integrate data from business systems, databases, APIs, files, and external sources using secure, scalable, and reusable engineering patterns. 

• Translate business and technical requirements into well-designed transformations, data models, shared datasets, semantic layers, and reusable data products. 

• Implement controls for data quality, validation, consistency, integrity, freshness, lineage, monitoring, exception handling, and reconciliation. 

• Establish and apply engineering practices for version control, testing, documentation, controlled releases, recovery, incident management, and production support. 

• Assess and continuously improve existing data flows and platform components for reliability, performance, availability, scalability, security, maintainability, resilience, and cost. 

• Work with IT Business Partners and business, analytics, architecture, AI, cybersecurity, and technology teams to clarify requirements, definitions, and dependencies and deliver practical data outcomes. 

• Contribute to the data platform roadmap, technical standards, reusable components, peer reviews, and architecture decisions, making clear recommendations and raising risks early. 

• Investigate and resolve data, pipeline, and platform issues, identify root causes, prevent repeated failures, and share knowledge with colleagues and delivery partners. 

• Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, or a related discipline, or equivalent practical experience. Relevant professional certifications are an advantage. 

• Typically 5+ years in data engineering, platform delivery, software engineering or a related field. 

• Proven hands-on experience independently designing, building, deploying, and supporting data platforms on Azure or a comparable cloud platform, including production pipelines, integrations, data products, or platform components. 

• Strong experience with data integration, transformation, modeling, programming and query languages, and modern data platform patterns. 

• Experience applying engineering and operational practices across data quality, testing, lineage, monitoring, security, performance, resilience, controlled releases, incident management, and production support. 

• Experience creating reusable data products, semantic models, and governed datasets for reporting, analytics, operational needs, automation, and AI. Experience working with unstructured or document-based data is an advantage. 

• Experience working across business and technical teams, troubleshooting complex data issues, and improving the reliability, performance, cost, and maintainability of data solutions. 

• Hands-on engineer with strong problem-solving, debugging, and delivery skills. 

• Proactive and accountable, with the judgment to work independently, keep delivery moving, and raise blockers early. 

• Pragmatic and quality-focused, willing to challenge weak data, unclear requirements, and unsustainable solutions. 

• Clear and collaborative communicator who shares knowledge, creates repeatable practices, and adapts as priorities and information evolve.